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A Universal Solution For Units - Invariance In Data Envelopment Analysis

Author

Listed:
  • Jin XU

    (China Center for Health Development Studies Peking University, Beijing, China)

  • Panagiotis ZERVOPOULOS

    (China Center for Health Development Studies Peking University, Beijing, China Department of Business Administration of Food and Agricultural Enterprises University of Ioannina, Agrinio, Greece)

  • Zhenhua QIAN

    (School of Social Science University of Science and Technology Beijing, China)

  • Gang CHENG

    (China Center for Health Development Studies Peking University, Beijing, China)

Abstract

The directional distance function model is a generalization of the radial model in data envelopment analysis (DEA). The directional distance function model is appropriate for dealing with cases where undesirable outputs exist. However, it is not a units-invariant measure of efficiency, which limits its accuracy. In this paper, we develop a data normalization method for DEA, which is a universal solution for the problem of units-invariance in DEA. The efficiency scores remain unchanged when the original data are replaced with the normalized data in the existing units-invariant DEA models, including the radial and slack-based measure models, i.e., the data normalization method is compatible with the radial and slack-based measure models. Based on normalized data, a units-invariant efficiency measure for the directional distance function model is defined.

Suggested Citation

  • Jin XU & Panagiotis ZERVOPOULOS & Zhenhua QIAN & Gang CHENG, 2012. "A Universal Solution For Units - Invariance In Data Envelopment Analysis," Theoretical and Practical Research in the Economic Fields, ASERS Publishing, vol. 3(2), pages 121-128.
    • Handle: RePEc:srs:jtpref:v:3:y:2012:i:2:p:121-128
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    References listed on IDEAS

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    More about this item

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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